Past Events
-
From Genome-Wide Association Studies to Biological Insights Using Integrative Molecular Epidemiology - Dr. Kraft
DCEG Seminar
Genome-wide association studies (GWAS) have identified thousands of common genetic variants robustly associated with risk of cancer, yet the biological mechanisms underlying these associations remain largely unknown, in part because of confounding by local correlation among variants, and in part because most of these variants are located in non-coding regions with poorly-understood functionality. Methods that integrate GWAS results with auxiliary data can suggest biological hypotheses for further in silico, in vitro and in vivo studies.
March 5, 2020 | 11:00 AM – 12:00 PMNCI Shady Grove TE 406 Rockville, Maryland -
Next Generation Statistical Methods in the Post-Genome Wide Association Studies - Dr. Chatterjee
Biostatistics Branch Seminar Series
In the early years of genome-wide association studies, data analysis primarily relied on fairly simplistic methods, such as running millions of univariate linear or logistic regressions, one for each genetic variant. Recently, however, as the sample sizes for some GWAS have become extremely large and various types of other genomic data have increasingly become available, analysis of such data has also become much more complex and statistically sophisticated.
March 4, 2020 | 10:30 AM – 11:30 AMNCI Shady Grove 6E032/034 Rockville, Maryland -
Longitudinal Data - Dr. Albert, Part 1 of 3
Biostatistics at the Frontier Seminar Series
Part 1 of 3 of the 2020 Biostatistics at the Frontier Seminar Series.
February 27, 2020 | 10:30 AM – 11:00 AMNCI Shady Grove TE 406 Rockville, Maryland -
Chasing Rainbows: Building a Career in Sexual and Gender Minority Health Equity Science - Dr. Kamen
Fellows' Cancer Health Disparities Interest Group
Dr. Kamen's research has focused on factors that lead to health disparities among sexual and gender minority populations, specifically disparities in cancer-related health outcomes and psychological distress
February 18, 2020 | 10:00 AM – 11:00 AMNCI Shady Grove 2E032/034 Rockville, Maryland -
Statistically Consistent Saliency Estimation - Dr. Barut
Biostatistics Branch Seminar Series
February 5, 2020 | 10:30 AM – 11:30 AMNCI Shady Grove 6E032/034 Rockville, Maryland -
Emerging Cancer Health Disparities - Dr. Gomez
Descriptive Epidemiology Seminar Series
Dr. Scarlett Lin Gomez is an epidemiologist with research interests in the role of social determinants of health, including race/ethnicity, socioeconomic status, gender, immigration status, sociocultural factors, and neighborhood contextual characteristics, on health outcomes.
January 23, 2020 | 10:30 AM – 11:30 AMNCI Shady Grove Seminar TE406 Rockville, M.D. -
Diet and Cancer: Harnessing Emerging Technologies to Advance Etiologic Research and Improve Nutritional Assessment - Dr. Loftfield
DCEG Stadtman Seminar
Diet and Cancer: Harnessing Emerging Technologies to Advance Etiologic Research and Improve Nutritional Assessment
January 22, 2020 | 11:00 AM – 12:00 PMNCI Shady Grove 2W910/912 Rockville, M.D. -
Comparing Alternatives for Estimation from Nonprobability Samples - Dr. Valliant
Biostatistics Branch Seminar Series
Three approaches to estimation from nonprobability samples are quasi-randomization, superpopulation modeling, and doubly-robust estimation. In the first, the sample is treated as if it was obtained via a probability mechanism but, unlike in probability sampling, that mechanism is unknown. Pseudo selection probabilities of being in the sample are estimated by using the sample in combination with some external data set that covers the desired population.
January 22, 2020 | 10:30 AM – 11:30 AMNCI Shady Grove 1W032/034 Rockville, Maryland -
Measuring the Mortality Reductions Produced by Organized Cancer Screening: A Principled Approach - Dr. Hanley
Biostatistics Branch Seminar Series
In cancer screening trials and population-based comparisons, mortality reductions are usually summarized by an overall (single-number) mortality reduction. This proportional hazards model is logically untenable. I describe a model Liu et al. (IntStatRev2015) for the expected reductions in each (Age,Year) cell of a Lexis diagram.
January 14, 2020 | 3:00 PM – 4:00 PMNCI Shady Grove 6E032/034 Rockville, M.D. -
Analysis of Extreme Conditional Quantiles - Dr. Wang
Biostatistics Branch Seminar Series
An important problem in many fields is the modeling and prediction of events that are rare but have significant consequences. Unexpectedly heavy rainfall, large portfolio loss, and dangerously low birth weight are some examples of rare events.
January 7, 2020 | 10:30 AM – 11:30 AMNCI Shady Grove 7E032/034 Rockville, M.D.